Method and system for hybrid network slicing

ABSTRACT

A method, a network device, and a non-transitory computer-readable storage medium are described in relation to a hybrid network slicing service. The hybrid network slicing service may enable the initial configuration of a network slice according to network slice requests that may include customized and user-specified network performance criteria. The hybrid network slicing service may enable network slice requests to specify selection of network resources and use/availability based on entity-based criteria including end device and/or application specific associations. The hybrid network slicing service may optimize network slice configurations and generate network slice templates.

BACKGROUND

Development and design of networks present certain challenges from anetwork-side perspective and an end device perspective. For example,Next Generation (NG) wireless networks, such as Fifth Generation NewRadio (5G NR) networks are being deployed and under development.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating an exemplary environment in which anexemplary embodiment of a hybrid network slicing service may beimplemented;

FIG. 2 is a diagram illustrating another exemplary environment in whichan exemplary embodiment of the hybrid network slicing service may beimplemented;

FIGS. 3A-3D are diagrams illustrating an exemplary process of anexemplary embodiment of the hybrid network slicing service;

FIG. 4 is a diagram illustrating exemplary components of a device thatmay correspond to one or more of the devices illustrated and describedherein; and

FIG. 5 is a flow diagram illustrating another exemplary process of anexemplary embodiment of the hybrid network slicing service.

DETAILED DESCRIPTION

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements. Also, the following detailed description does notlimit the invention.

Current network slicing models are based on two types of deploymentarchitectures. The first type is a network slice that may be configuredbased on an application and/or traffic category, such as ultra-reliablelow latency communication (URLLC), massive machine-type communication(mMTC), enhanced mobile broadband (eMBB), and so forth. The second typeof a network slice may be configured based on end device categories,such as an Internet of Things (IoT) category, a mobile virtual networkoperator (MVNO) category, a mobile broadband (MBB) category, asmartphone category, and so forth. According to these deployments, anetwork operator or another entity may make available a network slice tousers.

These current network slice architectures, however, assume equal ease inpartitioning of all resources, such as computational resources, radioresources, topological resources, storage resources, core networkresources, transmitter/receiver resources, bandwidth resources,communication link resources, and so forth. Additionally, these types ofnetwork slice architectures assume that the partitioning scheme isloss-less, efficient, and without any negative consequences. However,given the dynamism of resources and sharing of network resourcesvis-à-vis satisfying service level agreement (SLA) requirements,typically network systems may be unable to provision and/or maintain SLArequirements associated with network slices across multiple networksand/or end-to-end.

Additionally, the current network slice architectures do not allow forusers or other types of entities to request application-specific networkslices either prospectively or on-demand. As an example, a softwaredeveloper or another type of entity may wish to have a network sliceavailable to accommodate a new mobile application under development orto become publicly available to users. The entity may be unable tospecify SLA requirements to a network operator, for example, so thatnetwork slices may be prospectively and suitably configured andavailable to accommodate the SLA requirements. According to anotherexample, an end device may include a newly installed and newly available(e.g., to the public, customers, users, subscribers, etc.) application.Subsequent to the installation, the end device and/or the newlyinstalled application cannot, on-demand, request from a network, toconfigure a network slice that may accommodate SLA requirements of theapplication in which the SLA requirements may be unique relative tocurrent network slices offered and/or available by the network.

According to exemplary embodiments, a hybrid network slicing service isdescribed. The hybrid network slicing service may enable users torequest a network slice that may not otherwise be available and/oroffered by a network. According to an exemplary embodiment, the hybridnetwork slicing service may include a portal that allows the user tospecify parameters and values pertaining to the requested network slice.For example, the parameters and values may include SLA requirements. Asan example, the SLA requirements may specify one or multiple performancemetrics and values, such as those relating to latency, throughput,reliability, and/or another type of performance metric and value, asdescribed herein. Additionally, for example, the network slice requestmay specify other types of parameters and/or values relating to networkresources (e.g., dedicated, shared, etc.), prioritization, policies,and/or other types of criteria, as described herein.

According to an exemplary embodiment, network slices may be provisionedby domain. A domain may be associated with one or multiple entities. Forexample, a domain may be associated with a third party or a networkoperator and a third party. By way of further example, the hybridnetwork slicing service may provision and configure domain-specificnetwork slices that may be offered and/or available to domain specificend devices and/or applications. For example, the network slice may beapplication-specific (e.g., a single end device application versus acategory of an end device application). Such mapping(s) may be based onan association of an entity with the end devices, subscriber identitymodules (SIMS) or the like (e.g., cards), a user, and/or other context(e.g., location, etc.) pertaining to such elements, as described herein.The hybrid network slicing service may also “mix and match” rules and/orpolicies to make a network slice available to end users. Thedomain-specific network slices may be provisioned with domain-specificnetwork resources. For example, a network operator may allocate and/orreserve RAN and core network resources to an entity. A domain may havenetwork slices independent of other domains. According to variousexemplary embodiments, the network slice may be statistically configuredand maintained with the same resource levels for its lifetime ordynamically with on-demand setup and configured with adaptive resourcelevels.

According to an exemplary embodiment, the hybrid network slicing servicemay include an artificial intelligence and/or machine learning (AI/ML)device configured to receive a network slice request, as describedherein, and in response, test and learn a configuration for therequested network slice. As an example, the AI/ML, device may receive anetwork slice request from the software developer or another entity aspreviously described according to an exemplary scenario. The AI/MLdevice may learn and optimize a configuration for the network slice inthe network, as described herein. According to another exemplaryembodiment, the AI/ML device may provision and configure, on-demand, thenetwork slice. For example, the AI/ML device may receive a network slicefrom the end user that installed a new mobile application that has newlybecome available as previously described according to an exemplaryscenario. The AI/ML device may provision and configure a network slicethat may not have been previously available and/or offered by thenetwork.

According to an exemplary embodiment, the hybrid network slicing servicemay provide network slice configuration information to a networkprovisioning system. The network provisioning system may provision anetwork slice according to the network slice configuration information.According to an exemplary embodiment, the hybrid network slicing servicemay include the provisioning of radio access network (RAN) resources,core network resources, another type of network (e.g., a data network(DN), an external network relative to a RAN and/or a core network, anapplication layer network that hosts an application service, anintermediary network relative to end-to-end resources, etc.), end deviceresources, application server host resources, and the like. According toan exemplary embodiment, the mapping of an application service to anetwork operator-and-third party specific network slice may be doneindependently in each domain of a network.

According to an exemplary embodiment, the hybrid network slicing servicemay obtain current state information and use such information to learnand optimize the provisioning of the network slice, as described herein.For example, the AI/ML device may obtain and evaluate current stateinformation associated with a network and the network slice, determine anetwork performance, and modify or not modify the network sliceconfiguration, as described herein.

In view of the foregoing, the hybrid network slicing service may improvenetwork slice provisioning and afford a flexibility and diversificationof network slices available to users. Further, the hybrid networkslicing service may improve the management of network performance at anetwork element or geographic service area level based on AI/ML modelsand the feedback system, as described herein.

FIG. 1 is a diagram illustrating an exemplary environment 100 in whichan exemplary embodiment of a hybrid network slicing service may beimplemented. As illustrated, environment 100 includes an access network105, an external network 115, and a core network 120. Access network 105includes access devices 107 (also referred to individually or generallyas access device 107). External network 115 includes external devices117 (also referred to individually or generally as external device 117).Core network 120 includes core devices 122 (also referred toindividually or generally as core device 122). Environment 100 furtherincludes a portal device 125, a network performance device 127, anetwork provisioning device 129, and end devices 130 (also referred toindividually or generally as “end device 130”).

The number, type, and arrangement of networks illustrated in environment100 are exemplary. For example, according to other exemplaryembodiments, environment 100 may include fewer networks, additionalnetworks, and/or different networks. For example, according to otherexemplary embodiments, other networks not illustrated in FIG. 1 may beincluded, such as an X-haul network (e.g., backhaul, mid-haul,fronthaul, etc.), a transport network (e.g., Signaling System No. 7(SS7), etc.), or another type of network that may support a wirelessservice and/or an application service, as described herein.

A network device or a network function (referred to herein simply as anetwork device) may be implemented according to one or multiple networkarchitectures, such as a client device, a server device, a peer device,a proxy device, a cloud device, and/or a virtualized network device.Additionally, a network device may be implemented according to variouscomputing architectures, such as centralized, distributed, cloud (e.g.,elastic, public, private, etc.), edge, fog, and/or another type ofcomputing architecture, and may be incorporated into distinct types ofnetwork architectures (e.g., Software Defined Networking (SDN), virtual,logical, network slice, etc.). The number, the type, and the arrangementof network devices are exemplary. For example, two or more of portaldevice 125, network performance device 127, and network provisioningdevice 129 may be combined in whole or in part as a single networkdevice.

Environment 100 includes communication links between the networks andbetween the network devices. Environment 100 may be implemented toinclude wired, optical, and/or wireless communication links. Acommunicative connection via a communication link may be direct orindirect. For example, an indirect communicative connection may involvean intermediary device and/or an intermediary network not illustrated inFIG. 1 . A direct communicative connection may not involve anintermediary device and/or an intermediary network. The number, type,and arrangement of communication links illustrated in environment 100are exemplary.

Environment 100 may include various planes of communication including,for example, a control plane, a user plane, a service plane, and/or anetwork management plane. Environment 100 may include other types ofplanes of communication. A message communicated in support of the hybridnetwork slicing service may use at least one of these planes ofcommunication. Additionally, an interface of a network device may bemodified (e.g., relative to an interface defined by a standards body,such as Third Generation Partnership Project (3GPP), 3GPP2,International Telecommunication Union (ITU), European TelecommunicationsStandards Institute (ETSI), GSM Association (GSMA), and the like) or anew interface of the network device may be provided in order to supportthe communication (e.g., transmission and reception of messages, aninformation element (IE), an attribute value pair (AVP), an object, aheader, a parameter, or another form of a data instance) between networkdevices and the hybrid network slicing service logic of the networkdevice. According to various exemplary implementations, the interface ofthe network device may be a service-based interface, a referencepoint-based interface, an Open Radio Access Network (O-RAN) interface, a5G interface, another generation of interface (e.g., 5.5G, SixthGeneration (6G), Seventh Generation (7G), etc.), or some other type ofnetwork interface.

Access network 105 may include one or multiple networks of one ormultiple types and technologies. For example, access network 105 may beimplemented to include a 5G RAN, a future generation RAN (e.g., a 6GRAN, a 7G RAN, or a subsequent generation RAN), a centralized-RAN(C-RAN), an O-RAN, and/or another type of access network. Access network105 may include a legacy RAN (e.g., a Third Generation (3G) RAN, aFourth Generation (4G) or 4.5 RAN, etc.). Access network 105 maycommunicate with and/or include other types of access networks, such as,for example, a Wi-Fi network, a Worldwide Interoperability for MicrowaveAccess (WiMAX) network, a local area network (LAN), a Citizens BroadbandRadio System (CBRS) network, a cloud RAN, an O-RAN network, avirtualized RAN (vRAN), a self-organizing network (SON), a wired network(e.g., optical, cable, etc.), or another type of network that providesaccess to or can be used as an on-ramp to access network 105.

Access network 105 may include different and multiple functionalsplitting, such as options 1, 2, 3, 4, 5, 6, 7, or 8 that relate tocombinations of access network 105 and a core network including anEvolved Packet Core (EPC) network and/or an NG core (NGC) network (notillustrated), or the splitting of the various layers (e.g., physicallayer, media access control (MAC) layer, radio link control (RLC) layer,and packet data convergence protocol (PDCP) layer, etc.), planesplitting (e.g., user plane, control plane, etc.), interface splitting(e.g., F1-U, F1-C, E1, Xn-C, Xn-U, X2-C, Common Public Radio Interface(CPRI), etc.) as well as other types of network services, such as dualconnectivity (DC) or higher (e.g., a secondary cell group (SCG) splitbearer service, a master cell group (MCG) split bearer, an SCG bearerservice, non-standalone (NSA), standalone (SA), etc.), carrieraggregation (CA) (e.g., intra-band, inter-band, contiguous,non-contiguous, etc.), edge and core network slicing, coordinatedmultipoint (ColVIP), various duplex schemes (e.g., frequency divisionduplex (FDD), time division duplex (TDD), half-duplex FDD (H-FDD),etc.), and/or another type of connectivity service (e.g., NSA new radio(NR), SA NR, etc.).

According to some exemplary embodiments, access network 105 may beimplemented to include various architectures of wireless service, suchas, for example, macrocell, microcell, femtocell, picocell, metrocell,NR cell, Long Term Evolution (LTE) cell, non-cell, or another type ofcell architecture. Additionally, according to various exemplaryembodiments, access network 105 may be implemented according to variouswireless technologies (e.g., RATs, etc.), and various wirelessstandards, frequencies, bands, and segments of radio spectrum (e.g.,centimeter (cm) wave, millimeter (mm) wave, below 6 gigahertz (GHz),above 6 GHz, higher than mm wave, C-band, licensed radio spectrum,unlicensed radio spectrum, above mm wave), and/or other attributes ortechnologies used for radio communication. Additionally, oralternatively, according to some exemplary embodiments, access network105 may be implemented to include various wired and/or opticalarchitectures for wired and/or optical access services.

Depending on the implementation, access network 105 may include one ormultiple types of network devices, such as access devices 107. Forexample, access device 107 may include a gNB, an evolved Long TermEvolution (eLTE) evolved Node B (eNB), an eNB, a radio networkcontroller (RNC), a remote radio head (RRH), a baseband unit (BBU), aradio unit (RU), a remote radio unit (RRU), a centralized unit (CU), aCU-control plane (CP), a CU-user plane (UP), a distributed unit (DU), asmall cell node (e.g., a picocell device, a femtocell device, amicrocell device, a home eNB, etc.), an open network device (e.g., O-RANCentralized Unit (O-CU), O-RAN Distributed Unit (O-DU), O-RAN nextgeneration Node B (O-gNB), O-RAN evolved Node B (O-eNB)), a 5Gultra-wide band (UWB) node, a future generation wireless access device(e.g., a 6G wireless station, a 7G wireless station, or anothergeneration of wireless station), another type of wireless node (e.g., aWiFi device, a WiMax device, a hotspot device, etc.) that provides awireless access service, or another type of network device that providesa transport service (e.g., routing and forwarding), such as a router, aswitch, or another type of layer 3 (e.g., network layer of the OpenSystems Interconnection (OSI) model) network device. According to someexemplary implementations, access device 107 may include a combinedfunctionality of multiple RATs (e.g., 4G and 5G functionality, 5G and5.5G functionality, etc.) via soft and hard bonding based on demands andneeds. According to some exemplary implementations, access device 107may include an integrated functionality, such as a CU-CP and a CU-UP, orother integrations of split RAN nodes. Access device 107 may be anindoor device or an outdoor device.

According to various exemplary implementations, access device 107 mayinclude one or multiple sectors or antennas. The antenna may beimplemented according to various configurations, such as single inputsingle output (SISO), single input multiple output (SIMO), multipleinput single output (MISO), multiple input multiple output (MIMO),massive MIMO, three dimensional (3D) and adaptive beamforming (alsoknown as full-dimensional agile MIMO), two dimensional (2D) beamforming,antenna spacing, tilt (relative to the ground), radiation pattern,directivity, elevation, planar arrays, and so forth. Depending on theimplementation, access device 107 may provide a wireless access serviceat a cell, a sector, a sub-sector/zone, carrier, and/or otherconfigurable level. For example, the sub-sector/zone level may includemultiple divisions of a geographic area of a sector relative to accessdevice 107. By way of further example, the sector may be divided basedon proximity to the antenna of access device 107 (e.g., near, mid, far)and/or another criterion. According to another example, radio coverageof a location may be divided based on a Military Grid Reference System(MGRS) or another type of grid system to produce geo-bins. The sizeand/or shape of each geo-bin may be configurable. The size and/or theshape of a geo-bin may depend on the types of access device 107 (e.g.,eNB versus gNB), attributes of access device 107 (e.g., antennaconfiguration, radio frequency band of beam, etc.), and/or other factors(e.g., terrain of the radio covered locale).

According to an exemplary embodiment, at least some of access devices107 include logic of the hybrid network slicing service, as describedherein. For example, access device 107 may transmit and receive messagespertaining to the hybrid network slicing service, as described herein.For example, access device 107 may provide state information pertainingto access device 107 and other RAN-based network elements (e.g., cell,sector, sub-sector/zone, network slice segment, radio bearer, QoS flow,PDU session, protocol layer, etc.) to network performance device 127.Additionally, for example, access device 107 may be provisioned bynetwork provisioning device 129, as described herein.

External network 115 may include one or multiple networks of one ormultiple types and technologies that provides an application service.For example, external network 115 may be implemented using one ormultiple technologies including, for example, network functionvirtualization (NFV), software defined networking (SDN), cloudcomputing, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service(PaaS), Software-as-a-Service (SaaS), or another type of networktechnology. External network 115 may be implemented to include a cloudnetwork, a private network, a public network, a multi-access edgecomputing (MEC) network, a fog network, the Internet, a packet datanetwork (PDN), a service provider network, the World Wide Web (WWW), anInternet Protocol Multimedia Subsystem (IMS) network, a RichCommunication Service (RCS) network, a software-defined (SD) network, avirtual network, a packet-switched network, a data center, a datanetwork, or other type of network that may provide access to and mayhost an end device application service.

Depending on the implementation, external network 115 may includevarious network devices such as external devices 117. For example,external devices 117 may include virtual network devices (e.g.,virtualized network functions (VNFs), servers, host devices, applicationfunctions (AFs), application servers (ASs), server capability servers(SCSs), containers, hypervisors, virtual machines (VMs), networkfunction virtualization infrastructure (NFVI), and/or other types ofvirtualization elements, layers, hardware resources, operating systems,engines, etc.) that may be associated with application services for useby end devices 130. By way of further example, external devices 117 mayinclude mass storage devices, data center devices, NFV devices, SDNdevices, cloud computing devices, platforms, and other types of networkdevices pertaining to various network-related functions (e.g., security,management, charging, billing, authentication, authorization, policyenforcement, development, etc.). Although not illustrated, externalnetwork 115 may include one or multiple types of core devices 122, asdescribed herein.

External devices 117 may host one or multiple types of applicationservices. For example, the application services may pertain to broadbandservices in dense areas (e.g., pervasive video, smart office, operatorcloud services, video/photo sharing, etc.), broadband access everywhere(e.g., 50/100 Mbps, ultra-low-cost network, etc.), enhanced mobilebroadband (eMBB), higher user mobility (e.g., high speed train, remotecomputing, moving hot spots, etc.), Internet of Things (e.g., smartwearables, sensors, mobile video surveillance, smart cities, connectedhome, etc.), extreme real-time communications (e.g., tactile Internet,augmented reality (AR), virtual reality (VR), etc.), lifelinecommunications (e.g., natural disaster, emergency response, etc.),ultra-reliable communications (e.g., automated traffic control anddriving, collaborative robots, health-related services (e.g.,monitoring, remote surgery, etc.), drone delivery, public safety, etc.),broadcast-like services, communication services (e.g., email, text(e.g., Short Messaging Service (SMS), Multimedia Messaging Service(MMS), etc.), massive machine-type communications (mMTC), voice,conferencing, instant messaging), video streaming, and/or other types ofwireless and/or wired application services. External devices 117 mayalso include other types of network devices that support the operationof external network 115 and the provisioning of application services,such as an orchestrator, an edge manager, an operations support system(OSS), a local domain name system (DNS), registries, and/or externaldevices 117 that may pertain to various network-related functions (e.g.,security, management, charging, billing, authentication, authorization,policy enforcement, development, etc.). External devices 117 may includenon-virtual, logical, and/or physical network devices.

According to an exemplary embodiment, at least some of external devices117 may include logic of the hybrid network slicing service, asdescribed herein. For example, external device 117 may transmit andreceive messages pertaining to the hybrid network slicing service, asdescribed herein. For example, external device 117 may provide stateinformation pertaining to external device 117 and other externalnetwork-based network elements (e.g., container, virtual machine,application service, network slice segment, etc.) to network performancedevice 127. Additionally, for example, external device 117 may beprovisioned by network provisioning device 129, as described herein.

Core network 120 may include one or multiple networks of one or multiplenetwork types and technologies. Core network 120 may include acomplementary network of access network 105. For example, core network120 may be implemented to include a 5G core network, an EPC of an LTEnetwork, an LTE-Advanced (LTE-A) network, and/or an LTE-A Pro network, afuture generation core network (e.g., a 5.5G, a 6G, a 7G, or anothergeneration of core network), and/or another type of core network.

Depending on the implementation of core network 120, core network 120may include diverse types of network devices that are illustrated inFIG. 1 as core devices 122. For example, core devices 122 may include auser plane function (UPF), a Non-3GPP Interworking Function (N3IWF), anaccess and mobility management function (AMF), a session managementfunction (SMF), a unified data management (UDM) device, a unified datarepository (UDR), an authentication server function (AUSF), a networkslice selection function (NSSF), a network repository function (NRF), apolicy control function (PCF), a network data analytics function(NWDAF), a network exposure function (NEF), a service capabilityexposure function (SCEF), a lifecycle management (LCM) device, amobility management entity (MME), a packet data network gateway (PGW),an enhanced packet data gateway (ePDG), a serving gateway (SGW), a homeagent (HA), a General Packet Radio Service (GPRS) support node (GGSN), ahome subscriber server (HSS), an authentication, authorization, andaccounting (AAA) server, a policy and charging rules function (PCRF), apolicy and charging enforcement function (PCEF), and/or a chargingsystem (CS).

According to other exemplary implementations, core devices 122 mayinclude additional, different, and/or fewer network devices than thosedescribed. For example, core devices 122 may include a non-standard or aproprietary network device, and/or another type of network device thatmay be well-known but not particularly mentioned herein. Core devices122 may also include a network device that provides a multi-RATfunctionality (e.g., 4G and 5G, 5G and 5.5G, 5G and 6G, etc.), such asan SMF with PGW control plane functionality (e.g., SMF+PGW-C), a UPFwith PGW user plane functionality (e.g., UPF+PGW-U), and/or othercombined nodes (e.g., an HSS with a UDM and/or UDR, an MME with an AMF,etc.). Also, core devices 122 may include a split core device 122. Forexample, core devices 122 may include a session management (SM) PCF, anaccess management (AM) PCF, a user equipment (UE) PCF, and/or anothertype of split architecture associated with another core device 122, asdescribed herein.

According to an exemplary embodiment, at least some of core devices 122may include logic of the hybrid network slicing service, as describedherein. For example, core device 122 may transmit and receive messagespertaining to the hybrid network slicing service, as described herein.For example, core device 122 may provide state information pertaining tocore device 122 and other core-based network elements (e.g., QoS flow,network slice segment, session, protocol layer, etc.) to networkperformance device 127. Additionally, for example, access device 107 maybe provisioned by network provisioning device 129, as described herein.

Portal device 125 may include a network device that includes logic ofthe hybrid network slicing service, as described herein. Although portaldevice 125 is depicted outside of access network 105, external network115, and core network 120, such an illustration is exemplary. Accordingto other exemplary implementations, portal device 125 may reside in oneor multiple networks depicted and described herein. Additionally, portaldevice 125 may be implemented in a centralized, distributed, and/oranother type of network and/or computing architecture as a networkdevice or system, as described herein.

According to an exemplary embodiment, portal device 125 may beconfigured to receive a network slice request and provide the networkslice request to network performance device 127, as described herein.Portal device 125 may include a graphical user interface (GUI) thatallows a user to generate the network slice request. For example, theGUI may enable the user to select and specify SLA requirements (e.g.,performance metric parameters and values) and/or other types of criteria(e.g., domain, etc.), as described herein, that may be indicative of acharacteristic attributable to the requested network slice. According tovarious exemplary embodiments, the network slice request may beimplemented as a standalone message, a message associated with and/orincluded in a message of a network procedure (e.g., a PDU sessionestablishment procedure, a network attachment procedure, etc.), and/or aproprietary message. According to some exemplary embodiments, networkslice request information may also be provided to test devices, asdescribed herein.

Network performance device 127 may include a network device thatincludes logic of the hybrid network slicing service, as describedherein. Although network performance device 127 is depicted outside ofaccess network 105, external network 115, and core network 120, such anillustration is exemplary. According to other exemplary implementations,network performance device 127 may reside in one or multiple networksdepicted and described herein. Additionally, network performance device127 may be implemented in a centralized, distributed, and/or anothertype of network and/or computing architecture as a network device orsystem, as described herein.

According to an exemplary embodiment, network performance device 127 mayinclude AI/ML logic that calculates network slice configurationinformation. According to an exemplary embodiment, network performancedevice 127 may calculate the network slice configuration informationbased on the network slice request information, current analyticsinformation, network topology information, network state information,and/or test performance metric parameter values stemming from testtraffic, as described herein.

According to an exemplary embodiment, the network slice requestinformation may include performance metric parameters and values, asdescribed herein. The network slice request may include other types ofparameters and/or values. For example, the network slice request mayinclude an identifier that identifies a domain, as described. The domainmay also correlate to other aspects of a network slice, such as thenetwork resources that may be used (e.g., dedicated, shared, location ofresources, etc.) to provision the network slice, resourceprioritization, policies relating to various aspects of the networkslice, such as domain specific end devices and/or applications, servicelevel support, lifecycle management regarding virtualization, anidentifier that may identify an application and/or a service to whichthe performance metric parameters and values may pertain, traffic flowcharacteristics associated with the application and/or service (e.g.,continuous, bursty, periodic, aperiodic, amount of data, length of timepertaining to a transmission or a reception of data, etc.), executionbehavior of the application and/or service (e.g., backgroundapplication, foreground application, runs intermittently, runsconstantly, minimal end device resource usage, extensive end deviceresource usage, etc.), and/or other types of configurable criteria thatmay be of relevance for provisioning of the network slice, satisfyingperformance metrics/SLA requirements during an application session viathe network slice, and/or learning/optimizing a configuration for thenetwork slice.

According to an exemplary embodiment, network performance device 127 mayobtain current analytics information. For example, the current analyticsinformation may include performance metric parameters and valuesrelating to network elements and/or geographic areas within which aservice is provided. According to an exemplary embodiment, networkperformance device 127 may obtain the current analytics information froman NWDAF. According to other exemplary embodiments, network performancedevice 127 may obtain current analytics information from another type ofdevice that may provide real-time analytics data (e.g., a SON device).According to some exemplary embodiments, network performance device 127may obtain current analytics information from access device 107, coredevice 122, and/or external device 117. Network performance device 127may collect data, which may be statistical or real-time streaming fromvarious devices, such as the NWDAF, a SON, or another type of networkdevice.

According to various exemplary embodiments, the performance metricparameters and values may include key performance indicators (KPIs),Quality of Service (QoS) parameters and values, Quality of Experience(QoE) parameters and values, SLA parameters and values, and/or MeanOpinion Score (MOS) parameters and values. A performance metric valuemay be implemented as a single value (e.g., X) or a range of values(e.g., X to Y). The performance metric value may also be associated witha time period (e.g., seconds, hour(s), day(s), and/or another timeperiod), may indicate an average value, a mean value, and/or anotherstatistical value. By way of further example, the performance metricinformation may relate to the performance associated with user sessions,connections, channels, messaging, a network procedure (e.g., attachment,handover, session establishment, local breakout, dual connectivity,etc.), application services, and/or other types of metrics in relationto a network element and/or a geographic area associated with a service.The performance metric information may relate to user plane or userplane and control plane events or metrics. As an example, theperformance metric information may include information relating to RadioResource Control (RRC) setup failures, handover attempts, handoverfailures, radio bearer drops, uplink and/or downlink throughput, voicecall drops, random access failures, data volume (e.g., maximum, minimum,etc.), latency, packet error, delay, bit rates (e.g., guaranteed,maximum, minimum, burst, etc.), jitter, retries, 5G QoS ClassIdentifiers (QCIs) and characteristics, and so forth.

According to an exemplary embodiment, network performance device 127 mayobtain other types of data as a basis to calculate the network sliceconfiguration information, as described herein. For example, networkperformance device 127 may store or have access to network topologyinformation. The network topology information may indicate the type,number, and placement of access devices 107, external devices 117, andcore devices 122. The network topology information may include networkdevice identifiers, network slice identifiers, and/or other types ofunique identifiers. The network topology information may indicateconnectivity information pertaining to network devices and other typesof network elements (e.g., logical, virtual, network slices, links,etc.) of a network. The network topology information may includeinformation relating to components of access devices 107, such asantennas (e.g., height, number, type, gain, transmit loss, receive loss,receive signal, fade margin (e.g., thermal, effective, etc.), and othercharacteristics (e.g., carrier frequencies, frequency bands, cells,radio access technology (RAT), cell coverage, sector coverage,sub-sector/zone coverage) and configurations (e.g., CA, DC, CoMP, etc.).Similarly, the network topology information may include informationrelating to components of other types of network devices (e.g., coredevices 122, external devices 117, etc.) and/or communication links.

Additionally, network performance device 127 may obtain network stateinformation, which may relate to congestion levels, available networkresource capacities, and so forth. The network state information mayinclude current and/or predictive/prospective values. The network stateinformation may also include information that relates to network slices(e.g., the proposed network slice under development/configuration andother network slices provisioned in the network), and other types ofnetwork paths, traffic, network devices, and so forth, associated with anetwork.

According to some exemplary embodiments, network performance device 127may obtain performance metric parameters and value relating to testtraffic that traverses the proposed network slice under configurationaldevelopment. For example, a testing end device and a test server maygenerate uplink and/or downlink traffic, based on the network slicerequest information, such that performance metric parameters and valuesmay be measured in relation to the proposed network slice during initialprovisioning and learning towards optimizing a network sliceconfiguration.

Network performance device 127 may calculate values and/or configurationinformation pertaining to the network slice, as described herein, basedon a comparison of performance metric parameters and values (e.g., SLArequirements, etc., as specified in the network slice request) andcurrent analytics information pertaining to the network slice. Based ona result of the comparison, network performance device 127 may determinewhether a modification to the current network slice configuration is tobe calculated. As an example, when the current analytics informationsatisfies or exceeds the expected performance metric/SLA requirementinformation, network performance device 127 may determine to not modifynetwork resources and/or configurations associated with the networkslice. Alternatively, network performance device 127 may determine tomodify the allocation of network resources and/or configurationassociated with the network slice when the current analytics informationexceeds the expected performance metric/SLA requirement information. Forexample, network performance device 127 may reduce the allocation ofresources and/or adjust a configuration associated with a networkelement of relevance to the network slice. Further for example, when thecurrent analytics information fails to satisfy the expected performancemetric/SLA requirement information, network performance device 127 maydetermine to modify network resources and/or configuration so as tosatisfy or sustain the expected performance metric/SLA requirements.Network performance device 127 may make determinations regardingmodification, in addition to a result of the comparison, but also basedon policies and/or rules that may account for not only the expectedperformance metric parameters and values but also other information(e.g., historical information, etc.).

According to an exemplary embodiment, network performance device 127 mayinclude AI/ML logic, as described herein, to calculate the modificationto the current network slice configuration. The hybrid network slicingservice may enable network performance device 127 to tune one ormultiple network elements towards achieving and sustaining expectedperformance metrics associated with an SLA based on this feedback (e.g.,negative or positive) system, as described herein.

According to an exemplary embodiment, network performance device 127 mayprovide the network slice configuration information to networkprovisioning device 129. The network slice configuration information maypertain to the network slice (e.g., end-to-end), a segment of thenetwork slice, one or multiple network devices of the network slice, ageographic area associated with the network slice, and/or another typeof network element, for example. According to various exemplaryembodiments, network performance device 127 may be configured tocalculate and provide the network slice configuration informationaccording to a time schedule, or based on other criteria (e.g.,reactively, proactively, etc.). Network performance device 127 maypublish the network slice configuration information on a service bus,provide to third party devices of an application service layer networkvia a NEF and/or other types of network systems, such as an operationssupport system (OSS), a business support system (BSS), a networkmanagement system, an orchestrator, a radio intelligent controller (MC),virtualization management system, or the like.

Network provisioning device 129 may include a network device thatincludes logic of the hybrid network slicing service, as describedherein. Although network provisioning device 129 is depicted outside ofaccess network 105, external network 115, and core network 120, such anillustration is exemplary. According to other exemplary implementations,network provisioning device 129 may reside in one or multiple networksdepicted and described herein. Additionally, network provisioning device129 may be implemented in a centralized, distributed, and/or anothertype of network and/or computing architecture as a network device orsystem, as described herein. Network provisioning device 129 may beconfigured to provision the network slice, network elements of thenetwork slice, and network resources external from the network slice(e.g., other network slices, networks, network paths, network devices,etc.) according to the network slice configuration information receivedfrom network performance device 127.

End device 130 includes a device that may have communicationcapabilities (e.g., wireless, wired, optical, etc.). End device 130 mayor may not have computational capabilities. End device 130 may beimplemented as a mobile device, a portable device, a stationary device(e.g., a non-mobile device and/or a non-portable device), a deviceoperated by a user, or a device not operated by a user. For example, enddevice 130 may be implemented as a smartphone, a mobile phone, apersonal digital assistant, a tablet, a netbook, a phablet, a wearabledevice (e.g., a watch, glasses, etc.), a computer, a gaming device, amusic device, an IoT device, a drone, a smart device, a fixed wirelessdevice, a router, a sensor, an automated guided vehicle (AGV), anindustrial robot, or other type of wireless device (e.g., other type ofUE). End device 130 may be configured to execute various types ofsoftware (e.g., applications, programs, etc.). The number and the typesof software may vary among end devices 130. End device 130 may include“edge-aware” and/or “edge-unaware” application service clients. Forpurposes of description, end device 130 is not considered a networkdevice.

According to an exemplary embodiment, end device 130 may include logicof the hybrid network slicing service, as described herein. For example,end device 130 may transmit and receive messages pertaining to thehybrid network slicing service, as described herein. For example, enddevice 130 may provide state information pertaining to end device 130and other end device-based network elements (e.g., QoS flow, networkslice segment, PDU session, protocol layer, application service, networkslice, etc.) to network performance device 127. Additionally, forexample, end device 130 may be provisioned by network provisioningdevice 129, as described herein.

FIG. 2 is a diagram illustrating another exemplary environment 200 inwhich an exemplary embodiment of the hybrid network slicing service maybe implemented. As illustrated, environment 200 may include portaldevice 125, network performance device 127, network provisioning device129, a network 215, an NWDAF 220, a testing device 230, and end device130. Similar to the description of environment 100, the number, type,and arrangement of network devices, end devices 130, communicationlinks, and so forth, may be different in other embodiments.

Network performance device 127 may include an AI/ML system 205, asdescribed herein. AI/ML system 205 may include one or multiple types ofmodels. For example, the models may include a time series model, aforecast model, a clustering model, and/or a classification model. Themodels may include a tree-based algorithm, a regressive algorithm,and/or another type of AI/ML algorithm or logic, such as Naïve Bayes,K-Nearest Neighbors, decision tree, Random Forest, gradient boosting,support vector machine, clustering via embedding, a dense neuralnetwork, a convolutional neural network, a recurrent neural network,and/or the like. AI/ML system 205 may calculate network sliceconfiguration information pertaining to a network slice and/or ageographic area based on various types of information, as describedherein. Network provisioning device 129 may also use policies/rules,historical network performance information, network dependencyinformation associated with a network (e.g., access network 105, corenetwork 120, etc.), a network device (e.g., access device 107, coredevice 122, etc.), a network slice (e.g., 5QIs, etc.), a segment of anetwork slice, application services, and various network elements, asdescribed herein, to make this determination.

According to an exemplary embodiment, AI/ML system 205 may identifyparameters and generate templates that enable the provisioning ofnetwork resources and configurations such that expected performancemetric/SLA requirements of the network slice may be optimally modifiedwhen current analytics information (and other types of information) mayunderperform or when current analytics information may overperform. TheAI/ML logic may compare historical data sets to current networkconditions as a basis for selection of a template and associatedparameters and values that may be used. In this way, network performancedevice 127 may include logic that calculates for the provisionment,configuration, and modification of various types of network elementsand/or scopes of geographic areas that yields an optimization forconfiguration of the network slice according to one or multiple networkstates, geographic areas, domains, time period, network slice requestinformation, and/or other types of criteria, as described herein.

Network 215 may include access network 105, core network 120, externalnetwork 115, and/or other types of networks, as described herein. NWDAF220 may provide a function and/or a service in accordance with a networkstandard (e.g., 3GPP, 3GPP2, ITU, ETSI, GSMA, and/or the like) and/or ofa proprietary nature. For example, NWDAF 220 may collect data fromnetwork devices and operations, administration, and maintenance (OAM)systems across one or multiple networks or domains (e.g., core, cloud,etc.) via standard interfaces of a service-based architecture. NWDAF 220may obtain data (e.g., statistics, metric values, events, etc.) fromsuch devices/networks and may provide data analytics functions that maybe configured by a network operator, for example.

Additionally, for example, NWDAF 220 may include logic of an exemplaryembodiment of the hybrid network slicing service, as described herein.For example, NWDAF 220 may obtain current state information, which mayinclude current performance metric information, for various types andgranularities of network elements, geographic areas, and time periods(e.g., seconds, hour(s), day(s), and/or another time period) across oneor multiple networks, geographic service areas, and virtual/logicaldomains. NWDAF 220 may generate current network analytics informationand provide the current analytics information, which may include currentperformance metric parameters and values, as described herein, tonetwork performance device 127/AI/ML system 205. The current analyticsinformation may include current performance metric parameters andvalues. The current performance metric value may be implemented as asingle value (e.g., X) or a range of values (e.g., X to Y). The currentperformance metric value may also be associated with a time period, mayindicate an average value, a mean value, and/or another statisticalvalue. The current performance metric value may also be associated witha network element and/or a geographic service area, as described herein.

Testing device 230 may be implemented as end device 130. Testing device230 may be operated or controlled by an entity other than auser/subscriber, such as a network operator/administrator. Testingdevice 230 may generate data indicative of or pertaining to performanceof a network slice, a network element/resource of the network slice,and/or associated with a geographic service area or domain. For example,testing device 230 may perform testing for throughput, latency, and/oranother performance metric associated with the network slice. Testingdevice 230 may generate test traffic and transmit the test traffic viathe network slice or a portion thereof. Although not illustrated,network 215 may include testing device 230. For example, testing device230 in network 215 may be implemented as a network server.

FIGS. 3A-3D are diagrams illustrating an exemplary process 300 of anexemplary embodiment of the hybrid network slicing service. Asillustrated, referring to FIG. 3A, according to an exemplary scenario, auser (not illustrated) via end device 130 may provide network sliceinformation 302 to portal device 125. For example, network sliceinformation 302 may specify SLA requirements and other features of anetwork slice not available and/or offered by the network. For example,the proposed network slice may accommodate a new application (e.g., tobe launched or under development), as previously described. Based on thenetwork slice information, portal device 125 may generate a networkslice request 304 and transmit network slice request 304 to networkperformance device 127, as described herein.

According to another exemplary scenario, a user (not illustrated) viaend device 130 may transmit network slice information 302 in a message(e.g., as part of an attachment or PDU session establishment procedure).For example, the user may have installed an application, such as a newlyavailable (e.g., to the public, customers, users, subscribers, etc.)application on end device 130, and wishes to, on demand, request fromnetwork 215, to configure a network slice that may accommodateperformance metric/SLA requirements of the newly available applicationin which the SLA requirements may be unique relative to currentlyavailable network slices offered and/or available by network 215. As anexample, network slice information 302 may be relayed to portal device125 via core device 122 (e.g., an SMF, an AMF, or the like).

As further illustrated, network performance device 127 may receivecurrent analytics data 306 from NWDAF 220. In response, in block 310,AI/ML system 205 may analyze current analytics data 306 and networkslice request 304. AI/ML system 205 may determine to configure a networkslice based on network slice request 304.

Referring to FIG. 3B, AI/ML system 205 may calculate network sliceconfiguration information 315 based on the obtained data. For example,AI/ML system 205 may evaluate the identifier of the domain andcorrelated aspects of the proposed network slice, such as networkresources that may be used, application and traffic flowcharacteristics, performance metrics parameters and values, and soforth. AI/ML system 205 may evaluate current network state and analyticsinformation, as well as other information, as described herein.

Network performance device 127 may transmit network slice configurationinformation 317 to network provisioning device 129. Network provisioningdevice 129 may provision the network slice based on network sliceconfiguration information 320. For example, network provisioning device129 may identify the network elements and/or the geographic service areaof relevance for provisioning the network slice. Network provisioningdevice 129 may transmit network slice configuration information 322 tonetwork 215, and network 215 may provision the network slice 325.

Referring to FIG. 3C, after the provisioning of the network slice,network performance device 127 may receive current and past states ofthe network 330. According to some exemplary embodiments, networkperformance device 127 may receive test data 327. For example, networkslice configuration information 322 may include information that mayconfigure testing device 230, trigger the generation and/or transmissionof test data, provide a network slice identifier for the new networkslice, indicate a destination address associated with a network server,and so forth.

Based on the current analytics data 330 and/or test data 327, AI/MLsystem 205 may analyze and compare this information to an expectedperformance information 334, as described herein. Based on a result ofthe comparison, network performance device 127 may determine whetherexpected performance metric/SLA requirements associated with the networkslice are satisfied or not. As further illustrated, AI/ML system 205 maydetermine whether a network slice modification should be executed 337.As previously described, AI/ML system 205 may make this determinationbased on other information and factors, such as policies/rules,historical network performance information, and network dependencyinformation. Referring to FIG. 3D, according to this exemplary scenario,AI/ML system 205 may determine that a network modification should beexecuted, and in response, generate and transmit network slicemodification information 340 to network provisioning device 129. Forexample, AI/ML system 205 may select a template and associatedparameters that may optimally modify network resources and/orconfigurations such that expected network performance may beprospectively achieved by the network slice.

Network provisioning device 129 may provision the network slice based onthe network slice modification information 345. The provisioning mayinclude transmitting network slice modification information 347 tonetwork 215, and network 215 may re-provision the network slice 350.

According to other exemplary embodiments and scenarios, process 300 mayinclude additional operations, fewer operations, and/or differentoperations that may be performed. For example, network performancedevice 127 may determine that a network slice modification is notnecessary and operations 345 and 350 may not be performed.

FIG. 4 is a diagram illustrating exemplary components of a device 400that may be included in one or more of the devices described herein. Forexample, device 400 may correspond to access device 107, external device117, core device 122, network performance device 127, networkprovisioning device 129, end device 130, AI/ML system 205, NWDAF 220,testing device 230, and/or other types of devices, as described herein.As illustrated in FIG. 4 , device 400 includes a bus 405, a processor410, a memory/storage 415 that stores software 420, a communicationinterface 425, an input 430, and an output 435. According to otherembodiments, device 400 may include fewer components, additionalcomponents, different components, and/or a different arrangement ofcomponents than those illustrated in FIG. 4 and described herein.

Bus 405 includes a path that permits communication among the componentsof device 400. For example, bus 405 may include a system bus, an addressbus, a data bus, and/or a control bus. Bus 405 may also include busdrivers, bus arbiters, bus interfaces, clocks, and so forth.

Processor 410 includes one or multiple processors, microprocessors, dataprocessors, co-processors, graphics processing units (GPUs), applicationspecific integrated circuits (ASICs), controllers, programmable logicdevices, chipsets, field-programmable gate arrays (FPGAs), applicationspecific instruction-set processors (ASIPs), system-on-chips (SoCs),central processing units (CPUs) (e.g., one or multiple cores),microcontrollers, neural processing unit (NPUs), and/or some other typeof component that interprets and/or executes instructions and/or data.Processor 410 may be implemented as hardware (e.g., a microprocessor,etc.), a combination of hardware and software (e.g., a SoC, an ASIC,etc.), may include one or multiple memories (e.g., cache, etc.), etc.

Processor 410 may control the overall operation, or a portion ofoperation(s) performed by device 400. Processor 410 may perform one ormultiple operations based on an operating system and/or variousapplications or computer programs (e.g., software 420). Processor 410may access instructions from memory/storage 415, from other componentsof device 400, and/or from a source external to device 400 (e.g., anetwork, another device, etc.). Processor 410 may perform an operationand/or a process based on various techniques including, for example,multithreading, parallel processing, pipelining, interleaving, learning,model-based, etc.

Memory/storage 415 includes one or multiple memories and/or one ormultiple other types of storage mediums. For example, memory/storage 415may include one or multiple types of memories, such as, a random accessmemory (RAM), a dynamic RAM (DRAM), a static RAM (SRAM), a cache, a readonly memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM),an electrically EPROM (EEPROM), a single in-line memory module (SIMM), adual in-line memory module (DIMM), a flash memory (e.g., 2D, 3D, NOR,NAND, etc.), a solid state memory, and/or some other type of memory.Memory/storage 415 may include a hard disk (e.g., a magnetic disk, anoptical disk, a magneto-optic disk, a solid-state component, etc.), aMicro-Electromechanical System (MEMS)-based storage medium, and/or ananotechnology-based storage medium.

Memory/storage 415 may be external to and/or removable from device 400,such as, for example, a Universal Serial Bus (USB) memory stick, adongle, a hard disk, mass storage, off-line storage, or some other typeof storing medium. Memory/storage 415 may store data, software, and/orinstructions related to the operation of device 400.

Software 420 includes an application or a program that provides afunction and/or a process. As an example, with reference to AI/ML system205, software 420 may include an application that, when executed byprocessor 410, provides a function and/or a process of hybrid networkslicing service, as described herein. Additionally, for example, withreference to network provisioning device 129, software 420 may includean application that, when executed by processor 410, provides a functionand/or a process of hybrid network slicing service, as described herein.Software 420 may also include firmware, middleware, microcode, hardwaredescription language (HDL), and/or other form of instruction. Software420 may also be virtualized. Software 420 may further include anoperating system (OS) (e.g., Windows, Linux, Android, proprietary,etc.).

Communication interface 425 permits device 400 to communicate with otherdevices, networks, systems, and/or the like. Communication interface 425includes one or multiple wireless interfaces, optical interfaces, and/orwired interfaces. For example, communication interface 425 may includeone or multiple transmitters and receivers, or transceivers.Communication interface 425 may operate according to a protocol stackand a communication standard.

Input 430 permits an input into device 400. For example, input 430 mayinclude a keyboard, a mouse, a display, a touchscreen, a touchlessscreen, a button, a switch, an input port, a joystick, speechrecognition logic, and/or some other type of visual, auditory, tactile,affective, olfactory, etc., input component. Output 435 permits anoutput from device 400. For example, output 435 may include a speaker, adisplay, a touchscreen, a touchless screen, a light, an output port,and/or some other type of visual, auditory, tactile, etc., outputcomponent.

As previously described, a network device may be implemented accordingto various computing architectures (e.g., in a cloud, etc.) andaccording to various network architectures (e.g., a virtualizedfunction, PaaS, etc.). Device 400 may be implemented in the same manner.For example, device 400 may be instantiated, created, deleted, or someother operational state during its life cycle (e.g., refreshed, paused,suspended, rebooting, or another type of state or status), usingwell-known virtualization technologies. For example, access device 107,core device 122, external device 117, and/or another type of networkdevice or end device 130, as described herein, may be a virtualizeddevice.

Device 400 may perform a process and/or a function, as described herein,in response to processor 410 executing software 420 stored bymemory/storage 415. By way of example, instructions may be read intomemory/storage 415 from another memory/storage 415 (not shown) or readfrom another device (not shown) via communication interface 425. Theinstructions stored by memory/storage 415 cause processor 410 to performa function or a process described herein. Alternatively, for example,according to other implementations, device 400 performs a function or aprocess described herein based on the execution of hardware (processor410, etc.).

FIG. 5 is a flow diagram illustrating an exemplary process 500 of anexemplary embodiment of the hybrid network slicing service. According toan exemplary embodiment, network performance device 127 may perform astep of process 500. According to an exemplary embodiment, networkprovisioning device 129 may perform a step of process 500. According toan exemplary implementation, processor 410 executes software 420 toperform a step of process 500, as described herein. Alternatively, astep may be performed by execution of only hardware.

In block 505, network performance device 127 may receive a request for aproposed network slice. For example, network performance device 127 mayreceive a network slice request, which relates to a network slice thatis not offered and/or available by a network among the network slicesoffered by the network and available for use by users/end devices 130,as described herein. The network slice may relate to a new orunder-development application and/or service.

In block 510, network performance device 127 may receive currentanalytics information. For example, the current analytics informationmay include performance metric parameters and value information andnetwork state information, among other types of information, asdescribed herein.

In block 515, network performance device 127 may generate network sliceconfiguration information for the proposed network slice. For example,AI/ML system 205 may generate the network slice configurationinformation based on the network slice request, the current analyticsand state information, among other types of information, as describedherein.

In block 520, network provisioning device 129 may provision the proposednetwork slice based on the network slice configuration information.

In block 525, network performance device 127 may receive currentanalytics information. For example, AI/ML system 205 may receive thecurrent analytics and network state information, among other types ofinformation, as described herein, including performance metricinformation pertaining to the proposed network slice.

In block 530, network performance device 127 may compare an expectednetwork performance information of the proposed network slice to currentperformance network information. For example, AI/ML system 205 maydetermine whether the expected network performance of the proposednetwork slice is satisfied or not based on a result of the comparison.

In block 535, network performance device 127 may determine whether anetwork modification should be executed. For example, when the currentnetwork performance information may satisfy the expected networkperformance information, AI/ML system 205 may determine to not invoke anetwork modification (block 535-NO). Process 500 may return to block525. When the current network performance information may not satisfythe expected performance information, AI/ML system 205 may determine toinvoke a network modification (block 535-YES), in which AI/ML system 205may select and calculate network slice modifications (block 540). Forexample, AI/ML system 205 may select a network resource and/or aconfiguration associated with the network slice to modify according to amodel.

In block 545, network provisioning device 129 may invoke the networkslice modification. For example, network provisioning device 129 maytransmit the parameters and/or provision network resources and/ornetwork configurations. The network slice modification may be executedbased on the invocation. Process 500 may continue to block 525.

FIG. 5 illustrates an exemplary process of the hybrid network slicingservice, according to other exemplary embodiments, the hybrid networkslicing service may perform additional operations, fewer operations,and/or different operations than those illustrated and described. Forexample, AI/ML system 205 may determine when the network sliceconfiguration is satisfactorily learned and/or optimized, and maygenerate a network slice configuration template indicative of thelearned and optimized network slice configuration. AI/ML system 205 maycommunicate with other network systems for the assignment of networkslice assistance information, assignment of a network slice identifier,and so forth. The network slice may be available to users and enddevices 130 of a particular domain for use.

As set forth in this description and illustrated by the drawings,reference is made to “an exemplary embodiment,” “exemplary embodiments,”“an embodiment,” “embodiments,” etc., which may include a particularfeature, structure, or characteristic in connection with anembodiment(s). However, the use of the phrase or term “an embodiment,”“embodiments,” etc., in various places in the description does notnecessarily refer to all embodiments described, nor does it necessarilyrefer to the same embodiment, nor are separate or alternativeembodiments necessarily mutually exclusive of other embodiment(s). Thesame applies to the term “implementation,” “implementations,” etc.

The foregoing description of embodiments provides illustration but isnot intended to be exhaustive or to limit the embodiments to the preciseform disclosed. Accordingly, modifications to the embodiments describedherein may be possible. For example, various modifications and changesmay be made thereto, and additional embodiments may be implemented,without departing from the broader scope of the invention as set forthin the claims that follow. The description and drawings are accordinglyto be regarded as illustrative rather than restrictive.

The terms “a,” “an,” and “the” are intended to be interpreted to includeone or more items. Further, the phrase “based on” is intended to beinterpreted as “based, at least in part, on,” unless explicitly statedotherwise. The term “and/or” is intended to be interpreted to includeany and all combinations of one or more of the associated items. Theword “exemplary” is used herein to mean “serving as an example.” Anyembodiment or implementation described as “exemplary” is not necessarilyto be construed as preferred or advantageous over other embodiments orimplementations.

In addition, while a series of blocks has been described regarding theprocess illustrated in FIG. 5 , the order of the blocks may be modifiedaccording to other embodiments. Further, non-dependent blocks may beperformed in parallel. Additionally, other processes described in thisdescription may be modified and/or non-dependent operations may beperformed in parallel.

Embodiments described herein may be implemented in many different formsof software executed by hardware. For example, a process or a functionmay be implemented as “logic,” a “component,” or an “element.” Thelogic, the component, or the element, may include, for example, hardware(e.g., processor 410, etc.), or a combination of hardware and software(e.g., software 420).

Embodiments have been described without reference to the specificsoftware code because the software code can be designed to implement theembodiments based on the description herein and commercially availablesoftware design environments and/or languages. For example, diversetypes of programming languages including, for example, a compiledlanguage, an interpreted language, a declarative language, or aprocedural language may be implemented.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another, thetemporal order in which acts of a method are performed, the temporalorder in which instructions executed by a device are performed, etc.,but are used merely as labels to distinguish one claim element having acertain name from another element having a same name (but for use of theordinal term) to distinguish the claim elements.

Additionally, embodiments described herein may be implemented as anon-transitory computer-readable storage medium that stores data and/orinformation, such as instructions, program code, a data structure, aprogram module, an application, a script, or other known or conventionalform suitable for use in a computing environment. The program code,instructions, application, etc., is readable and executable by aprocessor (e.g., processor 410) of a device. A non-transitory storagemedium includes one or more of the storage mediums described in relationto memory/storage 415. The non-transitory computer-readable storagemedium may be implemented in a centralized, distributed, or logicaldivision that may include a single physical memory device or multiplephysical memory devices spread across one or multiple network devices.

To the extent the aforementioned embodiments collect, store, or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored, and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage and use of such information can besubject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as can be appropriatefor the situation and type of information. Collection, storage, and useof personal information can be in an appropriately secure mannerreflective of the type of information, for example, through variousencryption and anonymization techniques for particularly sensitiveinformation.

No element, act, or instruction set forth in this description should beconstrued as critical or essential to the embodiments described hereinunless explicitly indicated as such.

All structural and functional equivalents to the elements of the variousaspects set forth in this disclosure that are known or later come to beknown are expressly incorporated herein by reference and are intended tobe encompassed by the claims.

What is claimed is:
 1. A method comprising: receiving, by a networkdevice, a network slice request, which includes an identifier thatindicates first radio access network and first core network resourcesassociated with a first entity and second radio access network andsecond core network resources associated with a second entity, for aproposed network slice in a network; receiving, by the network device,first current network analytics information pertaining to the network;calculating, by the network device based on the first current networkanalytics information and the network slice request, a network sliceconfiguration for the proposed network slice; and provisioning, by thenetwork device, the proposed network slice in the network according tothe network slice configuration.
 2. The method of claim 1, wherein theproposed network slice has not been previously available nor offered bythe network.
 3. The method of claim 1, wherein the network slice requestincludes expected network performance parameters and values and whereinat least a portion of the first radio access network and first corenetwork resources are reserved.
 4. The method of claim 1, furthercomprising: receiving, by the network device after the provisioning,second current network analytics information pertaining to the proposednetwork slice; determining, by the network device, that expected networkperformance parameter values of the proposed network slice are notsatisfied based on the second current network analytics information; andmodifying, by the network device, the network slice configuration of theproposed network slice.
 5. The method of claim 1, wherein the proposednetwork slice pertains to an end device application or service underdevelopment.
 6. The method of claim 1, further comprising: generating,by the network device, a network slice template of the proposed networkslice.
 7. The method of claim 1, wherein the network slice request isreceived from a network portal that enables a user to specify expectednetwork performance parameters and values for the proposed networkslice.
 8. The method of claim 1, further comprising: invoking, by thenetwork device, transmission of test traffic data via the proposednetwork slice.
 9. A network device comprising: a processor that isconfigured to: receive a network slice request, which includes anidentifier that indicates first radio access network and first corenetwork resources associated with a first entity and second radio accessnetwork and second core network resources associated with a secondentity, for a proposed network slice in a network slice; receive firstcurrent network analytics information pertaining to the network;calculate, based on the first current network analytics information andthe network slice request, a network slice configuration for theproposed network slice; and provision the proposed network slice in thenetwork according to the network slice configuration.
 10. The networkdevice of claim 9, wherein the proposed network slice has not beenpreviously available nor offered by the network.
 11. The network deviceof claim 9, wherein the network slice request includes expected networkperformance parameters and values and wherein at least a portion of thefirst radio access network and first core network resources arereserved.
 12. The network device of claim 9, wherein the processor isfurther configured to: receive, after the provisioning, second currentnetwork analytics information pertaining to the proposed network slice;determine that expected network performance parameter values of theproposed network slice are not satisfied based on the second currentnetwork analytics information; and modify the network sliceconfiguration of the proposed network slice.
 13. The network device ofclaim 9, wherein the proposed network slice pertains to an end deviceapplication or service under development.
 14. The network device ofclaim 9, wherein the processor is further configured to: generate anetwork slice template of the proposed network slice.
 15. The networkdevice of claim 9, wherein the network slice request is received from anetwork portal that enables a user to specify expected networkperformance parameters and values for the proposed network slice. 16.The network device of claim 9, wherein the processor is furtherconfigured to: invoke transmission of test traffic data via the proposednetwork slice.
 17. A non-transitory computer-readable storage mediumstoring instructions executable by a processor of a network device,wherein the instructions are configured to: receive a network slicerequest, which includes an identifier that indicates first radio accessnetwork and first core network resources associated with a first entityand second radio access network and second core network resourcesassociated with a second entity, for a proposed network slice in anetwork; receive first current network analytics information pertainingto the network; calculate, based on the first current network analyticsinformation and the network slice request, a network slice configurationfor the proposed network slice; and provision the proposed network slicein the network according to the network slice configuration.
 18. Thenon-transitory computer-readable storage medium of claim 17, wherein theproposed network slice has not been previously available nor offered bythe network.
 19. The non-transitory computer-readable storage medium ofclaim 17, wherein the network slice request is received from a networkportal that enables a user to specify expected network performanceparameters and values for the proposed network slice.
 20. Thenon-transitory computer-readable storage medium of claim 17, wherein theinstructions are further configured to: generate a network slicetemplate of the proposed network slice.